Inferences in semi-parametric dynamic mixed models for longitudinal count data

Nan Zheng and Brajendra C. Sutradhar ()
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Nan Zheng: Memorial University
Brajendra C. Sutradhar: Memorial University

Annals of the Institute of Statistical Mathematics, 2018, vol. 70, issue 1, No 9, 215-247

Abstract: Abstract This paper considers a semi-parametric mixed model for longitudinal counts under the assumption that for conditional on a common random effect over time the repeated count responses of an individual follow a Poisson AR(1) (auto-regressive order 1) non-stationary correlation structure. A step-by-step estimation approach is developed which provides consistent estimators for the non-parametric function, regression parameters, variance of the random effects, and auto-correlation structure of the model. Proofs for the consistency properties of the estimators along with their convergence rates are derived. A simulation study is conducted to examine first the estimation effects on parameters when the non-parametric function is ignored, and then an overall estimation study is carried out in the presence of the non-parametric function by including its estimation as well.

Keywords: Consistency; Dynamic relationship for repeated counts; Generalized quasi-likelihood; Longitudinal correlations; Overdispersion of main interest; Parametric and non-parametric functions; Random effects and their variance; Regression effects of main interest; Semi-parametric model and estimation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10463-016-0590-9

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